PowerPoint Presentation

Post-Crash Noninvasive Occupant Monitoring for Emergency Response

Kevin Joseph and Kristofer D. Kusano, Ph.D.Center of Injury Biomechanics, Virginia Tech Wake Forest University, Blacksburg VABackground CDC studies on traumatic brain injuries(TBI):Risk of death decreases by 25% when a seriously injured patient is treated at a trauma center vs a local hospitalOnly 27% of 1.5 million TBI go to a trauma centerCar crashes are the second leading cause of TBI and leader of TBI deaths

GCS is difficult to test autonomously because of painful stimuli.Accurately detects unconscious and stable occupants only because of the lack of many GCS motor tests Has to estimate GCS motor based off other vitals and sensor

Weight has to be calibrated based off seat and sitting position for exact occupant weight since voltage conversion yields weight being pushed onto the sensor

Heart Rate frequency/signal weak and varied but still valid

Non-invasive occupant monitoring shows promise for post-crash injury assessment.

Listening

Move in seat back and forwardUnbuckle and buckle seatbeltPress button on steering wheel123456MotorMakes no movementsExtension to painful stimuliAbnormal flexion to painful stimuliFlexion to painful stimuliLocalizes painful stimuliObeys commands12345EyeDoes not open eyesOpens eyes in response topainful stimuliOpens eyes in response to voiceOpens eyes spontaneouslyVerbalMakes no soundsIncomprehensible soundsUtters inappropriate wordsConfused, disorientedOriented, converses normallyGCS program is a GUI that will be displayed in a car. It will display different pages that will poise different challenges to test responsiveness and assign a score via different car mechanicsFilter pressure signal with a 4th order Butterworth low pass filter at three Hz: Weight: 0.1Hz; Respiratory: 3Hz; Heart: 10HzAim: Design a system to continuously monitor vital signs and test for consciousnessWeightRespiratory RateHeart RateGlasgow Coma Scale(GCS)GCS is used to test the level of TBI and consciousness with a score from 3(Unconscious) to 15(Stable)Composed of Motor, Verbal, and Eye SectionsUse these vital signs to help the car diagnose the occupants condition in order to speed emergency medical response from the medical responders and/or car.Method:All Vital Signs: MATLAB program that features data acquisition, filtering, and different tests to extrapolate proper value for each vital signGCS Testing: Self-Coded Java Graphical User Interface(GUI) for occupant testing combined with MATLAB program for diagnostics of scores.Biomechanics REU Virginia Tech School of Biomedical EngineeringNational Science FoundationIMARI (Increasing Minority Admissions into Research Institutions)Oakwood Biology DepartmentNIH Grant: 1R25GM106994-01

Listening

Move in seat back and forwardUnbuckle and buckle seatbeltPress button on steering wheel

---> Chronological order of GCS testing --->Tests eye and verbal responsiveness and control

Uses a visual prompt and a microphone Visual display first Verbal Prompt if there is no responseTests motor responsiveness and physical control

Uses various car mechanics to sense physical responseOCS Seat SensorSteering WheelSeatbelt, etc.

System OverviewAbstract/AimIntroduction

Respiratory RateHeart RateGlasgow Coma ScaleAcknowledgementsConclusionDiagnosesDiagnosing runs every time new vitals or GCS score is acquired assessmentStarts with Unconscious Test, then Severe Injury Test, and ending with Minor Injury TestHas the ability to recognize if vitals have changed or there was a miscalculation and then restart the algorithm via Misdiagnosed diagnoses

Uses the previously acquired vitals as metrics to base parameters for each diagnosesUnstable: pulse not between 50 and 100, weak breaths, light headed and pain or headachesUndiagnosable: no weight in seat, volatile readings, or misdiagnosed 3 timesExtreme Blood Loss: major weight drop over time, and increased average heart rate variability and pulse from starting average

Uses a self adjusted IQR test to remove outliers Copies the lowest quartile to the opposite side to lower the IQR value Done because of small dataset and one number can largely extend the outlier range123123b3a130.523.225.611.66.523.225.630.520.815.9